In the futile hope that maybe, just maybe, folks’ views about welfare policy might just stand to be informed by data, here are a few testable hypotheses I’ve seen floating around. They posit things that are knowable, and I’m sure data exists to resolve things. Let’s walk through a few of them.
First, how do poor people use money? I tend to say we ought to just give money to poor people if we want to make poor people better off. Other folks think that they’ll just waste it on booze and cigarettes rather than helping their kids. I don’t discount that that’s also possible; it’s an empirical question.
Now why does this matter? If you think that parents will waste money given them, you might prefer in-kind benefits provided directly to the children of poor parents rather than cash transfers. School breakfast programmes can fall into that category, despite that they’re rather ineffective and largely go towards feeding kids who would have been fed anyway. I think that some of the support for wrecking the GST by exempting merit goods also comes from this kind of view, though I think this rather misguided: vouchers for merit goods could be a rather less ruinous way of achieving the desired end.
So, the test. Get household consumption survey data, look for some shock to benefit payments, and check the effects on different consumption categories. If extra money going to poor households disproportionately increases consumption of lotto tickets and booze, then the paternalists who want to make sure that money given to the poor is used for particular things are right in wishing for more in-kind benefits; if not, then the paternalists should back down on such assertions.
I can’t imagine that this empirical test has not been done by somebody somewhere; I just don’t know the results.
It would be interesting data. I don’t know if there would be data for NZ. There hasn’t been any real change to benefit levels since 1991, and I suspect that changes to benefit levels often occur at the same time as other changes – so overall consumption data may have multiple factors changing it.
But the next one may be testable.
Second, “can’t feed ‘em, don’t breed ‘em”. Twitter and the NZ blogs have a bunch of folks yelling at each other about whether the main problem in child poverty stems from poor people’s unwillingness to engage the prudential constraint or whether it’s bad luck. Those on the right note that if poor people stopped having kids they couldn’t afford, then child poverty would be less of an issue. People on the left instead remind those on the right that birth control can fail and that people in good financial circumstances can fall on hard times for reasons outside of their control and after they’ve set their family size.
So, a test. Start with DPB numbers. What is the current fertility rate of women receiving the Domestic Purposes Benefit, and how does it compare to the fertility rate of women of similar age and marital status who are not receiving government support for the raising of children? If the fertility rate among women on the Domestic Purposes Benefit is roughly what we would expect given known rates of contraception failure, then score a point for the left. If women on government support are instead choosing to have more children while in poverty, then score a point for the right. I would bet that the data shows rather more childbearing than would be expected from contraception failure alone, but less than the fertility rates among similar-aged women not on the DPB, but I’ve not seen the data.
This data should exist, and be testable. Anyone know if it has been tested anywhere? What is the fertility rate of women on the DPB and women not on the DPB?Tags: Eric Crampton